What does positive predictive value indicate?

What does positive predictive value indicate?

• A. The probability that a person has the disease given a positive test result.
• B. The probability that a person does not have the disease given a negative result.
• C. The probability of true negatives.
• D. The likelihood that the test is reliable regardless of disease.

Answer: (A)

Positive predictive value is the probability that a person truly has the disease given a positive test result. It’s computed as the number of true positives divided by all positive results (true positives plus false positives). This value shows how likely a positive test really indicates disease and depends on how common the disease is in the population as well as how accurate the test is. For example, with a rare disease, even a test with good sensitivity and specificity can yield many false positives, lowering the PPV. The other statements describe different concepts: the probability of not having the disease given a negative result is the negative predictive value; true negatives refer to the portion of correctly identified non-disease cases (related to specificity); and a general claim about the test’s reliability regardless of disease isn’t a standard predictive metric since predictive values depend on disease status.

Positive predictive value is the probability that a person truly has the disease given a positive test result. It’s computed as the number of true positives divided by all positive results (true positives plus false positives). This value shows how likely a positive test really indicates disease and depends on how common the disease is in the population as well as how accurate the test is. For example, with a rare disease, even a test with good sensitivity and specificity can yield many false positives, lowering the PPV. The other statements describe different concepts: the probability of not having the disease given a negative result is the negative predictive value; true negatives refer to the portion of correctly identified non-disease cases (related to specificity); and a general claim about the test’s reliability regardless of disease isn’t a standard predictive metric since predictive values depend on disease status.